If you have followed my recent work, it is no surprise that I have been attempting to explain player injury profiles. I’ll be honest – injuries are mostly random events that are very difficult to predict in a statistical model with accuracy or reliability. While the recent remodel of sports injury predictor is a large step in the right direction, I place my faith in the building of metrics that seek to describe the player’s prior injury history.
My heart behind this project was simple: I want to wade into a topic that is ignored and misunderstood. While fantasy football has had several medical doctors provide insights on individual injuries, none have been able to apply combine both the medical and statistical perspective. Due to this void, I was recently commissioned to by sports injury predictor (SIP) in attempt to apply clinical relevance to a machine learning procedure. As an epidemiologist, one of the primary objectives was to use the duality of my professional training to build metrics that aids in the accuracy of SIP’s predictive models. This led me to the development of the following metrics: Durability Score and Susceptibility Score.
Latest posts by Jeremy Funk (see all)
- The Top Five Durable Players by Position: Part Two - September 9, 2017
- The Top Five Durable Players by Position: Part One - September 6, 2017
- What are the Durability and Susceptibility Metrics? - July 16, 2017